Zobrazeno 1 - 10
of 1 759
pro vyhledávání: '"Le, Hung"'
Autor:
To, Long Truong, Le, Hung Tuan, Nguyen, Dat Van-Thanh, Nguyen, Manh Trong, Nguyen, Tri Thien, Van Huynh, Tin, Van Nguyen, Kiet
Large Language Models (LLMs), with gradually improving reading comprehension and reasoning capabilities, are being applied to a range of complex language tasks, including the automatic generation of language data for various purposes. However, resear
Externí odkaz:
http://arxiv.org/abs/2411.05641
Determining the difficulty of a text involves assessing various textual features that may impact the reader's text comprehension, yet current research in Vietnamese has only focused on statistical features. This paper introduces a new approach that i
Externí odkaz:
http://arxiv.org/abs/2411.04756
Pre-trained on massive amounts of code and text data, large language models (LLMs) have demonstrated remarkable achievements in performing code generation tasks. With additional execution-based feedback, these models can act as agents with capabiliti
Externí odkaz:
http://arxiv.org/abs/2411.04329
Autor:
Chang, Hsien-Chih, Cohen-Addad, Vincent, Conroy, Jonathan, Le, Hung, Pilipczuk, Marcin, Pilipczuk, Michał
Cohen-Addad, Le, Pilipczuk, and Pilipczuk [CLPP23] recently constructed a stochastic embedding with expected $1+\varepsilon$ distortion of $n$-vertex planar graphs (with polynomial aspect ratio) into graphs of treewidth $O(\varepsilon^{-1}\log^{13} n
Externí odkaz:
http://arxiv.org/abs/2411.00216
Effective decision-making in partially observable environments demands robust memory management. Despite their success in supervised learning, current deep-learning memory models struggle in reinforcement learning environments that are partially obse
Externí odkaz:
http://arxiv.org/abs/2410.10132
Autor:
Denton, Will, Chiavetta, Lilly, Bryant, Michael, Shah, Vedarsh, Zhu, Rico, Weerts, Ricky, Xue, Phillip, Chen, Vincent, Le, Hung, Lin, Maxwell, Camacho, Austin, Council, Drew, Horowitz, Ethan, Ong, Jackie, Chu, Morgan, Pool, Alex
The Duke Robotics Club is proud to present our robot for the 2023 RoboSub Competition: Oogway. Oogway marks one of the largest design overhauls in club history. Beyond a revamped formfactor, some of Oogway's notable features include all-new computer
Externí odkaz:
http://arxiv.org/abs/2410.10900
Autor:
Denton, Will, Bryant, Michael, Chiavetta, Lilly, Shah, Vedarsh, Zhu, Rico, Xue, Philip, Chen, Vincent, Lin, Maxwell, Le, Hung, Camacho, Austin, Galvez, Raul, Yang, Nathan, Ren, Nathanael, Rose, Tyler, Chu, Mathew, Ergashev, Amir, Arya, Saagar, Pieter, Kaelyn, Horowitz, Ethan, Allampallam, Maanav, Zheng, Patrick, Kaarls, Mia, Wood, June
The Duke Robotics Club is proud to present our robot for the 2024 RoboSub Competition: Oogway. Now in its second year, Oogway has been dramatically upgraded in both its capabilities and reliability. Oogway was built on the principle of independent, w
Externí odkaz:
http://arxiv.org/abs/2410.09684
Euclidean spanners are important geometric objects that have been extensively studied since the 1980s. The two most basic "compactness'' measures of a Euclidean spanner $E$ are the size (number of edges) $|E|$ and the weight (sum of edge weights) $\|
Externí odkaz:
http://arxiv.org/abs/2409.08227
Ahmed, Bodwin, Sahneh, Kobourov, and Spence (WG 2020) introduced additive spanners for weighted graphs and constructed (i) a $+2W_{\max}$ spanner with $O(n^{3/2})$ edges and (ii) a $+4W_{\max}$ spanner with $\tilde{O}(n^{7/5})$ edges, and (iii) a $+8
Externí odkaz:
http://arxiv.org/abs/2408.14638
In their pioneering work, Chan, Har-Peled, and Jones (SICOMP 2020) introduced locality-sensitive ordering (LSO), and constructed an LSO with a constant number of orderings for point sets in the $d$-dimensional Euclidean space. Furthermore, their LSO
Externí odkaz:
http://arxiv.org/abs/2408.14617